Impacts of low-disturbance dairy manure incorporation on ammonia and greenhouse gas fluxes in a corn silage-winter rye cover crop system.

Manure and fertilizer applications contribute to greenhouse gas (GHG) and ammonia (NH ) emissions. Losses of NH and nitrous oxide (N O) are an economic loss of nitrogen (N) to farms, and methane (CH ), N O, and carbon dioxide (CO ) are important GHGs. Few studies have examined the effects of low-disturbance manure incorporation (LDMI) on both NH and GHG fluxes.

Introduction to the Biophotonics Congress 2020 feature issue.

The guest editors introduce a feature issue containing papers based on research presented at the OSA Biophotonics Congress (the former BIOMED) 20-23 April 2020, in the first all virtual, web conference format undertaken by OSA.

Identifying the mechanisms of cation inhibition of phenol oxidation by acid birnessite.

Many phenolic compounds found as contaminants in natural waters are susceptible to oxidation by manganese oxides. However, there is often variability between oxidation rates reported in pristine matrices and studies using more environmentally relevant conditions. For example, the presence of cations generally results in slower phenolic oxidation rates.

Global Concerns with B Vitamin Statuses: Biofortification, Fortification, Hidden Hunger, Interactions, and Toxicity.

The prevalence of undernutrition due to insufficient energy intake has been reduced by nearly 50% since 1990. This reduction is largely attributed to improved yields of staple crops, such as wheat, rice, and maize; however, these improvements did little for micronutrient deficiencies that affect an estimated two billion people worldwide. Starchy staple crops are energy dense but are often lacking in one or more B vitamins, making resource-constrained people who consume monotonous diets comprised predominantly of these staples at risk for developing deficiency.

Rewiring yeast metabolism to synthesize products beyond ethanol.

Saccharomyces cerevisiae, Baker's yeast, is the industrial workhorse for producing ethanol and the subject of substantial metabolic engineering research in both industry and academia. S. cerevisiae has been used to demonstrate production of a wide range of chemical products from glucose.

Genetic control of root anatomical plasticity in maize.

Root anatomical phenes have important roles in soil resource capture and plant performance; however, their phenotypic plasticity and genetic architecture is poorly understood. We hypothesized that (a) the responses of root anatomical phenes to water deficit (stress plasticity) and different environmental conditions (environmental plasticity) are genetically controlled and (b) stress and environmental plasticity are associated with different genetic loci than those controlling the expression of phenes under water-stress and well-watered conditions. Root anatomy was phenotyped in a large maize (Zea mays L.

Natural variation for carotenoids in fresh kernels is controlled by uncommon variants in sweet corn.

Sweet corn (Zea mays L.) is highly consumed in the United States, but does not make major contributions to the daily intake of carotenoids (provitamin A carotenoids, lutein and zeaxanthin) that would help in the prevention of health complications. A genome-wide association study of seven kernel carotenoids and twelve derivative traits was conducted in a sweet corn inbred line association panel ranging from light to dark yellow in endosperm color to elucidate the genetic basis of carotenoid levels in fresh kernels.

Training Population Optimization for Genomic Selection.

Training populations can be optimized for specific testing populations. Optimized training populations are smaller, more related, and more predictive. Stratified sampling with a relationship matrix weighted by marker effect is optimal.

Expected Genotype Quality and Diploidized Marker Data from Genotyping-by-Sequencing of Urochloa spp. Tetraploids.

Introduced concept of expected genotype quality (EGQ) and software to calculate it Provided read depth guidelines for GBS in tetraploids Developed software to generate diploidized genotype calls from VCF files Demonstrated value of aligning GBS reads to a mock reference genome for SNP discovery Recommend filtering based on GQ and read depth to prevent genotype bias Although genotyping-by-sequencing (GBS) is a well-established marker technology in diploids, the development of best practices for tetraploid species is a topic of current research. We determined the theoretical relationship between read depth and the phred-scaled probability of genotype misclassification conditioned on the true genotype, which we call expected genotype quality (EGQ). If the GBS method has 0.

Novel determination of effective freeze-thaw cycles as drivers of ecosystem change.

Soil freeze-thaw cycles (FTCs) profoundly influence biophysical conditions and modify biogeochemical processes across many northern-hemisphere and alpine ecosystems. How FTCs will contribute to global processes in seasonally snow-covered ecosystems in the future is of particular importance as climate change progresses and winter snowpacks decline. Our understanding of these contributions is limited because there has been little consideration of inter- and intrayear variability in the characteristics of FTCs, in part due to a limited appreciation for which of these characteristics matters most with respect to a given biogeochemical process.

Impacts of groundwater extraction on calcareous fen floristic quality.

Groundwater withdrawal has increased over the past several decades throughout the U.S. Upper Midwest, yet impacts of pumping on groundwater-dependent wetlands remain understudied.

Neutralization of high pH and alkalinity effluent from recycled concrete aggregate by common subgrade soil.

Use of recycled concrete aggregate (RCA) as highway basecourse material conserves virgin aggregate, reduces energy consumption and CO emissions, and may also decrease costs during construction. However, concerns remain over possible negative environmental impacts associated with high pH (>11) effluent from RCA in contact with water. This study examines the reactive transport of high-pH and high-alkalinity water, modeled on RCA leachate, through model subgrade soils.

Model-driven analysis of mutant fitness experiments improves genome-scale metabolic models of Zymomonas mobilis ZM4.

Genome-scale metabolic models have been utilized extensively in the study and engineering of the organisms they describe. Here we present the analysis of a published dataset from pooled transposon mutant fitness experiments as an approach for improving the accuracy and gene-reaction associations of a metabolic model for Zymomonas mobilis ZM4, an industrially relevant ethanologenic organism with extremely high glycolytic flux and low biomass yield. Gene essentiality predictions made by the draft model were compared to data from individual pooled mutant experiments to identify areas of the model requiring deeper validation.

Conditional Recurrent Flow: Conditional Generation of Longitudinal Samples with Applications to Neuroimaging.

We develop a conditional generative model for longitudinal image datasets based on sequential invertible neural networks. Longitudinal image acquisitions are common in various scientific and biomedical studies where often each image sequence sample may also come together with various secondary (fixed or temporally dependent) measurements. The key goal is not only to estimate the parameters of a deep generative model for the given longitudinal data, but also to enable evaluation of how the temporal course of the generated longitudinal samples are influenced as a function of induced changes in the (secondary) temporal measurements (or events).

Sampling-free Uncertainty Estimation in Gated Recurrent Units with Applications to Normative Modeling in Neuroimaging.

There has recently been a concerted effort to derive mechanisms in vision and machine learning systems to offer uncertainty estimates of the predictions they make. Clearly, there are benefits to a system that is not only accurate but also has a sense for when it is not. Existing proposals center around Bayesian interpretations of modern deep architectures - these are effective but can often be computationally demanding.

Metabolic mapping of glioblastoma stem cells reveals NADH fluxes associated with glioblastoma phenotype and survival.

Significance: Glioblastoma multiforme (GBM) is the most frequently diagnosed adult primary brain malignancy with poor patient prognosis. GBM can recur despite aggressive treatment due to therapeutically resistant glioblastoma stem cells (GSCs) that may exhibit metabolic plasticity.

Aim: Intrinsic nicotinamide adenine dinucleotide (NADH) fluorescence can be acquired with fluorescence lifetime imaging microscopy (FLIM) to examine its bound and free metabolic states in GSC and GBM tissues.

Super-resolution recurrent convolutional neural networks for learning with multi-resolution whole slide images.

We study a problem scenario of super-resolution (SR) algorithms in the context of whole slide imaging (WSI), a popular imaging modality in digital pathology. Instead of just one pair of high- and low-resolution images, which is typically the setup in which SR algorithms are designed, we are given multiple intermediate resolutions of the same image as well. The question remains how to best utilize such data to make the transformation learning problem inherent to SR more tractable and address the unique challenges that arises in this biomedical application.

Optical fiber-based dispersion for spectral discrimination in fluorescence lifetime imaging systems.

The excited state lifetime of a fluorophore together with its fluorescence emission spectrum provide information that can yield valuable insights into the nature of a fluorophore and its microenvironment. However, it is difficult to obtain both channels of information in a conventional scheme as detectors are typically configured either for spectral or lifetime detection. We present a fiber-based method to obtain spectral information from a multiphoton fluorescence lifetime imaging (FLIM) system.

Effect of Fractionation and Chemical Characteristics on the Crystallization Behavior of Milk Fat.

The experiments reported in this study provided a more comprehensive insight into the effect of chemical composition on the crystallization behavior of milk fat (MF). MF was fractionated between 20 and 40 °C into nine fractions with different melting points and was first subjected to the heating step (L20, L30, L40, and S40) followed by the cooling phase (SS40, SL40, SS30, SL30, and LL40). Furthermore, the species of fatty acids (FAs) and triglycerides (TAGs) of the MF fractions were identified.

Interlaboratory Measurement of Rheological Properties of Tomato Salad Dressing.

Rheological properties of food materials are important as they influence food texture, processing properties, and stability. Rotational rheometry has been widely used for measuring rheological properties. However, the measurements obtained using different geometries and rheometers are generally not compared for precision and accuracy, so it is difficult to compare data across different studies.

The Effect of Overrun, Fat Destabilization, and Ice Cream Mix Viscosity on Entire Meltdown Behavior.

This study aims at exploring ice cream meltdown behavior by changing the levels of stabilizer (ST), polysorbate 80 (PS80), and overrun (OR). By adjusting the formulation of ice cream, the degree of fat destabilization (FD), mix viscosity (MV), and overrun can be controlled within a certain range, which in turn presents different meltdown behaviors for study. In addition to the drip-through test, the shape of ice cream as it melts was recorded as height change to further investigate ice cream meltdown.

Spatial and temporal variation of ecosystem properties at macroscales.

Although spatial and temporal variation in ecological properties has been well-studied, crucial knowledge gaps remain for studies conducted at macroscales and for ecosystem properties related to material and energy. We test four propositions of spatial and temporal variation in ecosystem properties within a macroscale (1000 km's) extent. We fit Bayesian hierarchical models to thousands of observations from over two decades to quantify four components of variation - spatial (local and regional) and temporal (local and coherent); and to model their drivers.

Prototype system for interventional dual-energy subtraction angiography.

Dual-energy subtraction angiography (DESA) using fast kV switching has received attention for its potential to reduce misregistration artifacts in thoracic and abdominal imaging where patient motion is difficult to control; however, commercial interventional solutions are not currently available. The purpose of this work was to adapt an x-ray angiography system for 2D and 3D DESA. The platform for the dual-energy prototype was a commercially available x-ray angiography system with a flat panel detector and an 80 kW x-ray tube.

Proceedings of the second biennial Cleveland Neural Engineering Workshop 2013.

The Cleveland Neural Engineering Workshop (NEW) is a biennial meeting started in 2011 as an "unconference" to bring together leaders in the neural engineering and related fields. Since the first iteration of the meeting, NEW has evolved from "just getting together" to a more important purpose of creating, reviewing, and promoting a uniform strategic roadmap for the field. The purpose of this short report, as well as the companion 2015 and 2017 reports, is to provide a historical record of this meeting and the evolution of the roadmap.